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https://dx.doi.org/10.48550/ar...
Article . 2008
License: arXiv Non-Exclusive Distribution
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Detrended fluctuation analysis of traffic data

Authors: Xiaoyan Zhu; Zonghua Liu; Ming Tang;

Detrended fluctuation analysis of traffic data

Abstract

Different routing strategies may result in different behaviors of traffic on internet. We analyze the correlation of traffic data for three typical routing strategies by the detrended fluctuation analysis (DFA) and find that the degree of correlation of the data can be divided into three regions, i.e., weak, medium, and strong correlation. The DFA scalings are constants in both the regions of weak and strong correlation but monotonously increase in the region of medium correlation. We suggest that it is better to consider the traffic on complex network as three phases, i.e., the free, buffer, and congestion phase, than just as two phases believed before, i.e., the free and congestion phase.

4 pages, 4 figures

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Keywords

Computer Science - Networking and Internet Architecture, Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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